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Interpolation inequalities in W1,p(S1) and carré du
champ methods
Jean Dolbeault, Marta Garcia-Huidobro, Raul Manásevich
To cite this version:
Jean Dolbeault, Marta Garcia-Huidobro, Raul Manásevich. Interpolation inequalities in W1,p(S1) and
carré du champ methods. Discrete and Continuous Dynamical Systems - Series A, American Institute
of Mathematical Sciences, 2020, 40 (1), pp.375-394. �10.3934/dcds.2020014�. �hal-02003141v2�
(S
AND CARR ´E DU CHAMP METHODS
Jean Dolbeault∗
CEREMADE (CNRS UMR n◦7534) PSL university, Universit´e Paris-Dauphine Place de Lattre de Tassigny, 75775 Paris 16, France
Marta Garc´ıa-Huidobro
Departamento de Matem´aticas Pontificia Universidad Cat´olica de Chile Casilla 306, Correo 22, Santiago de Chile, Chile
R´aul Man´asevich
DIM & CMM (UMR CNRS n◦2071)
FCFM, Universidad de Chile Casilla 170 Correo 3, Santiago, Chile
Abstract. This paper is devoted to an extension of rigidity results for non-linear differential equations, based on carr´e du champ methods, in the one-dimensional periodic case. The main result is an interpolation inequality with non-trivial explicit estimates of the constants in W1,p(S1) with p ≥ 2. Mostly
for numerical reasons, we relate our estimates with issues concerning periodic dynamical systems. Our interpolation inequalities have a dual formulation in terms of generalized spectral estimates of Keller-Lieb-Thirring type, where the differential operator is now a p-Laplacian type operator. It is remarkable that the carr´e du champ method adapts to such a nonlinear framework, but sig-nificant changes have to be done and, for instance, the underlying parabolic equation has a nonlocal term whenever p 6= 2.
1. Introduction. This paper is a generalization to p 6= 2 of results which have been established in [5] in the case p = 2 and go back to [10]. On the other hand, we use a flow interpretation which was developed in [7] and relies on the carr´e du champ method. This second approach gives similar results and can be traced back to [4,3]. As far as we know, Bakry-Emery techniques have been used in the context of the p-Laplacian operator to produce estimates of the first eigenvalue but neither for non-linear (i.e., p 6= 2) interpolation inequalities nor for estimates on non-linear p-Laplacian flows. By mixing the two approaches, we are able not only to establish inequalities with accurate estimates of the constants but we also obtain improved inequalities and get quantitative rates of convergence for a nonlinear semigroup associated with the p-Laplacian. We also establish improved rates of convergence,
2010 Mathematics Subject Classification. Primary 35J92; 35K92. Secondary: 49K15; 58J35. Key words and phrases. Interpolation; Gagliardo-Nirenberg inequalities; bifurcation; branches of solutions; elliptic equations; p-Laplacian; entropy; Fisher information; carr´e du champ method; Poincar´e inequality; rigidity; uniqueness; rescaling; period; nonlinear Keller-Lieb-Thirring energy estimates.
at least as long as the solution does not enter the asymptotic regime. Results are similar to those of [9] in the case p = 2.
Let us denote by S1 the unit circle which is identified with [0, 2π), with periodic boundary conditions and by dσ = dx2π the uniform probability measure on S1. We
define λ?1:= inf v∈W1 kv0k2 Lp(S1) kvk2 L2(S1) and λ1:= inf v∈W1 kv0k2 Lp(S1) kvk2 Lp(S1)
where the infimum is taken on the set W1 of all functions v in W1,p(S1) \ {0} such
thatR
S1v dσ = 0. Here we use the notation:
kukLp(S1):= Z S1 |u|pdσ 1/p .
With our notations, λp/21 is the lowest positive eigenvalue of the p-Laplacian operator Lp defined by
− Lpv := − |v0|p−2v0
0 . Since dσ is a probability measure, then kuk2Lp(S1)− kuk
2
L2(S1) has the same sign as
(p − 2), so that
(p − 2) λ?1− λ1 ≥ 0 .
See AppendixAfor further considerations. Our main result goes as follows.
Theorem 1. Assume that p ∈ (2, +∞) and q > p − 1. There exists Λp,q> 0 such
that for any function u ∈ W1,p(S1), the following inequalities hold: ku0k2 Lp(S1)≥ Λp,q p − q kuk2 Lp(S1)− kuk 2 Lq(S1) (1) if p 6= q, and ku0k2Lp(S1)≥ 2 pΛp,pkuk 2−p Lp(S1) Z S1 |u|p log |u| kukLp(S1) dσ (2)
if p = q and u 6≡ 0. Moreover, the sharp constant Λp,q in (1) and (2) is such that
λ1≤ Λp,q≤ λ?1.
Inequality (2) is an Lplogarithmic Sobolev inequality which is reminiscent of, for
instance, [6]. A Taylor expansion that will be detailed in the proof of Proposition1
(also see Proposition3and Section2.5) shows that (1) and (2) tested with u = 1+ε v and v ∈ W1are equivalent at order ε2to kv0k2Lp(S1)≥ λ?1kvk2L2(S1), which would not be true if, for instance, we were considering ku0kα
Lp(S1) with α 6= 2. This explains why we have to consider the square of the norms in the inequalities and not other powers, for instance α = 1 or α = p. This is also the reason why λ1and λ?1 are not
defined as the standard first positive eigenvalue of the p-Laplacian operator. In 1992, L. V´eron considered in [13] the equation
− Lpu + |u|q−2u = λ |u|p−2u
not only on S1but also on general manifolds and proved that it has no solution in W1,p(S1) except the constant functions if λ ≤ λp/21 and 1 < p < q. Let us point out that, up to constants that come from the various norms involved in (1), the corresponding Euler-Lagrange equation is the same equation when q < p, while in
the case q > p, the Euler-Lagrange equation of our problem is, again up to constants that involve the norms, of the form
− Lpu + λ |u|p−2u = |u|q−2u .
This paper is organized as follows.
• In Section2, we start by proving Theorem1in the case 2 < p < q with estimates for elliptic equations. The key estimate is the Poincar´e type estimate of Lemma1, which is used in Section2.3to prove Proposition2. The adaptations needed to deal with the case q < p are listed in Section2.4.
• Section3 is devoted to further results and consequences. In Section3.1, we give an alternative proof of Theorem1based on a method for parabolic equations. This is the link with the carr´e du champ methods. The parabolic setting provides a framework in which the computations of Section2 can be better interpreted. An-other consequence of the parabolic approach is that a refined estimate is established by taking into account terms that are simply dropped in the elliptic estimates of Section 2: see Section 3.2. A last result deals with ground state energy estimates for nonlinear Schr¨odinger type operators, which generalize to the case of the p-Laplacian the Keller-Lieb-Thirring estimates known when p = 2: see Section 3.3. Notice that such Keller-Lieb-Thirring estimates are completely equivalent to the interpolation inequalities of Theorem1, including for optimality results.
• Numerical results which illustrate our main theoretical results have been col-lected in Section4. The computations are relatively straightforward because, after a rescaling, the bifurcation problem (described below in Sections 2.1 and2.4) can be rephrased as a dynamical system such that all quantities associated with critical points can be computed in terms of explicit integrals.
2. Proof of the main result. The goal of this section is to prove Theorem1and some additional results. The emphasis is put on the case 2 < p < q, while the other cases are only sketched. We shall collect a series of observations before proving Theorem1 in Section2.5.
2.1. A variational problem. On S1, let us assume that p < q and define
Qλ[u] :=
ku0k2
Lp(S1)+ λ kuk2Lp(S1) kuk2
Lq(S1) for any λ > 0. Let
µ(λ) := inf
u∈W1,p(S1)\{0}Qλ[u] .
In the range p < q, inequality (1) can be embedded in the larger family of inequalities ku0k2
Lp(S1)+ λ kuk2Lp(S1)≥ µ(λ) kuk2Lq(S1) ∀ u ∈ W1,p(S1) (3) so that the optimal constant Λp,q of Theorem1 can be characterized as
Λp,q = (q − p) infλ > 0 : µ(λ) < λ .
Proposition 1. Assume that 1 < p < q. On (0, +∞), the function λ 7→ µ(λ) is concave, strictly increasing, such that µ(λ) < λ if λ > λ?
1/(q − p).
Proof. The concavity is a consequence of the definition of µ(λ) as an infimum of affine functions of λ. If µ(λ) = λ, then the equality is achieved by constant functions. If we take
u = 1 + ε v with Z
S1
as a test function for Qλand let ε → 0, then we get Qλ[1 + ε v] − λ ∼ ε2 kv0k2 Lp(S1)− λ (q − p) kvk2L2(S1) .
Let us take an optimal v for the minimization problem corresponding to λ?1, so that
the r.h.s. becomes proportional to λ?1− λ (q − p). As a consequence, we know that
µ(λ) < λ if λ > λ?
1/(q − p).
By standard methods of the calculus of variations, we know that the infimum µ(λ) is achieved for any λ > 0 by some a.e. positive function in W1,p
(S1). As
a consequence, we know that there exists a non-constant positive solution to the Euler-Lagrange equation if λ > λ?
1/(q − p). Notice that all non-zero constants are
also solutions in that case. The equation can be written as − ku0k2−pLp(S1)Lpu + λ kuk 2−p Lp(S1)u p−1 = µ(λ) kuk2−q Lq(S1)u q−1. (4)
What we want to prove is that (4) has no non-constant solution for λ > 0, small enough, and give an estimate of this rigidity range.
Proposition 2. Assume that 2 < p < q and λ > 0. All positive solutions of (4) are constant if λ ≤ λ1/(q − p).
The proof of this result is given in Section2.3. As a preliminary step, we establish a Poincar´e estimate.
2.2. A Poincar´e estimate. Let us consider the Poincar´e inequality kv0k2
Lp(S1)− λ1kvkL2p(S1)≥ 0 ∀ v ∈ W1,
which is a consequence of the definition of λ1.
Lemma 1. Assume that p > 2. Then for any non-negative u ∈ W2,p(S1) \ {0}, we have Z S1 u2−p(Lpu)2dσ ≥ λ1 ku0k2(p−1) Lp(S1) kukp−2Lp(S1) . (5)
Moreover λ1 is the sharp constant.
Proof. By expanding the square, we know that 0 ≤ Z S1 u2−p Lpu + C |u|p−2(u − ¯u) 2 dσ = Z S1 u2−p(Lpu)2dσ − C ku0k p Lp(S1) − C ku0kpLp(S1)− C Z S1 |u|p−2(u − ¯u)2dσ . With C = λ1 ku0kp−2 Lp(S1) kukp−2Lp(S1) , v = u − ¯u and u =¯ Z S1 u dσ , we know that Z S1 u2−p kuk2−pLp(S1) (Lpu)2dσ − λ1ku0k 2(p−1) Lp(S1) ≥ λ1ku0k 2(p−2) Lp(S1) ku 0k2 Lp(S1)− λ1 Z S1 |u|p−2 kukp−2Lp(S1) v2dσ ! .
Assuming that p > 2, H¨older’s inequality with exponents p/(p − 2) and p/2 shows that Z S1 |u|p−2 kukp−2Lp(S1) v2dσ ≤ kuk2−pLp(S1) Z S1 |u|p−2p−2p dσ p−2p kvk2 Lp(S1)= kvk2Lp(S1).
We observe that v is in W1 so that λ1kvk2Lp(S1)≤ kv0k
2 Lp(S1)and λ1 Z S1 |u|p−2v2dσ ≤ ku0k2 Lp(S1)kuk p−2 Lp(S1) (see (16) for further considerations). Hence we conclude that
Z S1 u2−p kuk2−pLp(S1) (Lpu)2dσ − λ1ku0k 2(p−1) Lp(S1) ≥ λ1ku0k 2(p−2) Lp(S1) kv0k2 Lp(S1)− λ1kvk2Lp(S1) ≥ 0 . The fact that λ1is optimal is obtained by considering the equality case in the above
inequalities. See details in AppendixA.
2.3. A first rigidity result. We adapt the strategy of [5,10] when p = 2 to the case p > 2 using the Poincar´e estimate of Section2.2.
Proof of Proposition2. Let us consider a positive solution to (4). If we multiply (4) by − u2−pL
pu and integrate on S1, we obtain the identity
ku0k2−pLp(S1) Z S1 u2−p(Lpu)2dσ + λ kuk 2−p Lp(S1) Z S1 |u0|pdσ = (1 + q − p) µ(λ) kuk2−qLq(S1) Z S1 uq−p|u0|pdσ . If we multiply (4) by (1+q −p) u1−p|u0|p
and integrate on S1, we obtain the identity
− ku0k2−pLp(S1)(1 + q − p) Z S1 u1−pLpu |u0|pdσ + λ kuk2−pLp(S1)(1 + q − p) Z S1 |u0|pdσ = (1 + q − p) µ(λ) kuk2−qLq(S1) Z S1 uq−p|u0|pdσ .
By subtracting the second identity from the first one, we obtain that ku0k2−pLp(S1) Z S1 u2−p(Lpu)2dσ + (1 + q − p) Z S1 u1−pLpu |u0|pdσ − λ (q − p) kuk2−pLp(S1) Z S1 |u0|pdσ = 0 .
After an integration by parts, the above identity can be rewritten as Z S1 u2−p(Lpu)2dσ + (1 + q − p) (p − 1)2 2 p − 1 Z S1 |u0|2p up dσ − λ (q − p)ku 0kp−2 Lp(S1) kukp−2Lp(S1) Z S1 |u0|pdσ = 0 .
By Lemma1, this proves that λ1− λ (q − p) ku 0k2(p−1) Lp(S1) kukp−2Lp(S1) + (1 + q − p) (p − 1) 2 2 p − 1 Z S1 |u0|2p up dσ ≤ 0 .
If λ ≤ λ1/(q − p), this proves that u is a constant. This completes the proof of
Proposition2.
2.4. An extension of the range of the parameters. So far we have considered only the case q > p. Let us consider the case 1 < q < p and define, in that case,
Qµ[u] := ku 0k2
Lp(S1)+ µ kuk2Lq(S1) kuk2
Lp(S1) for any µ > 0. Let
λ(µ) := inf
u∈W1,p(S1)\{0}Q
µ[u] .
If µ(λ) = λ, then the equality is achieved by constant functions. In the range p > q, inequality (1) can be embedded in the larger family of inequalities
ku0k2Lp(S1)+ µ kuk 2 Lq(S1)≥ λ(µ) kuk 2 Lp(S1) ∀ u ∈ W 1,p (S1) (6)
so that the optimal constant Λp,q of Theorem1 can be characterized as
Λp,q= (p − q) infµ > 0 : λ(µ) < µ .
As in Section2.1, a Taylor expansion allows us to prove the following result.
Proposition 3. Assume that 1 < q < p. The function µ 7→ λ(µ) is concave, strictly increasing, such that λ(µ) < µ if µ > λ?
1/(p − q).
As a consequence of Proposition3, there exists a non-constant positive solution to the Euler-Lagrange equation if µ > λ?
1/(p − q). This equation can be written as
− ku0k2−pLp(S1)Lpu + µ kuk 2−q Lq(S1)u q−1= λ(µ) kuk2−p Lp(S1)u p−1. (7)
There is also a range in which the only solutions are constants.
Proposition 4. Assume that p > 2 and p − 1 < q < p. All positive solutions of (7) are constant if µ ≤ λ1/(q − p).
Proof. The computation is exactly the same as in the proof of Proposition2, except that λ and µ(λ) have to be replaced by −λ(µ) and −µ respectively.
Z S1 u2−p(Lpu)2dσ + (1 + q − p) (p − 1)2 2 p − 1 Z S1 |u0|2p up dσ − λ (p − q)ku 0kp−2 Lp(S1) kukp−2Lp(S1) Z S1 |u0|pdσ = 0 .
The conclusion then holds by Lemma1 as in the case q > p, except that we need to ensure that the factor (1 + q − p) is positive.
2.5. The interpolation inequalities.
Proof of Theorem 1. Inequality (1) follows from Inequalities (3) and (6) with Λp,q:=(q − p) minλ > 0 : µ(λ) < λ if 2 < p < q ,
Λp,q:=(p − q) minµ > 0 : λ(µ) < µ if p > 2 and p − 1 < q < p ,
and from Propositions1 and 2 if p < q, or from Propositions3 and 4 if p > q. It remains to consider the limit case as q → p. By passing to the limit in the right hand side, we obtain the Lp logarithmic Sobolev inequality (2). The upper bound Λp,p≤ λ?1is easily checked by computing
ku0εk2 Lp(S1)− 2 pλ kuεk 2−p Lp(S1) Z S1 |uε|plog |uε| kuεkLp(S1) dσ = ε2(λ∗1− λ)kvk2 L2(S1)+ o(ε2) where uε = 1 + ε v and v is an optimal function for the minimization problem
corresponding to λ?
1. This completes the proof of Theorem1.
3. Further results and consequences. In this section we collect a list of results which go beyond the statement of Theorem 1. Let us start with an alternative proof of this result which paves the route to an improved interpolation inequality, compared to inequality (1).
3.1. The parabolic point of view. As in [7], the method of Section 2.3 can be rephrased using a parabolic evolution equation in the framework of the carr´e du champ method. The elliptic computations of Section2.3 can be interpreted as a special case corresponding to stationary solutions. Here we shall consider the 1-homogenous p-Laplacian flow
∂u ∂t = ku0k2−p Lp(S1) kuk2−pLp(S1) u2−p Lpu + (1 + q − p) |u0|p u . (8)
The main originality compared to previous results based on the carr´e du champ method is that a nonlocal term involving the norms ku0kLp(S1)and kukLp(S1)has to be introduced in order to obtain a linear estimate of the entropy, defined as
e(t) := kuk2
Lp(S1)− kuk2Lq(S1) p − q
if p 6= q, in terms of the Fisher information i(t) := ku0k2
Lp(S1). If u is a positive solution of (8), we first observe that
d dt Z S1 uqdσ = q ku0k2−p Lp(S1) kuk2−pLp(S1) Z S1 u1+q−p Lpu + (1 + q − p) |u0|p u dσ = 0 . Hence kuk2Lq(S1)does not depend on t and we may assume without loss of generality
that kuk2Lq(S1)= 1. After an integration by parts,
e0= d e dt = 2 ku0k2−p Lp(S1) p − q Z S1 u Lpu + (1 + q − p) |u0|p u dσ = − 2 i
if p 6= q. A similar computation shows that e0 = − 2 i is also true when p = q, provided we define the entropy by
e(t) :=2 pkuk 2−p Lp(S1) Z S1 |u|p log |u| kukLp(S1) dσ in that case, with i := ku0k2
Lp(S1)as before.
One more derivation along the flow shows that i0 =d i dt = − 2 ku0k2(2−p) Lp(S1) kuk2−pLp(S1) Z S1 Lpu u2−p Lpu + (1 + q − p) |u0|p u dσ . Using an integration by parts, we have
Z S1 Lpu u2−p |u0|p u dσ = (p − 1)2 2 p − 1 Z S1 |u0|2p up dσ ≥ 0 .
With the help of Lemma1, we conclude that
i0≤ − 2 λ1i − 2 (1 + q − p) (p − 1)2 2 p − 1 ku0k2(2−p) Lp(S1) kuk2−pLp(S1) Z S1 |u0|2p up dσ ≤ − 2 λ1i . (9)
Let us explain why this computation provides us with a second proof of Theorem1. A positive solution of (8) is such that i(t) ≤ i(0) e− 2 λ1t for any t ≥ 0 and thus limt→+∞i(t) = 0. We will see next that limt→+∞e(t) = 0. As kuk2Lq(S1) = 1, for each n ∈ N, there exists xn∈ [0, 2π) such that u(xn, n) = 1, hence
|u(x, n) − 1| = |u(x, n) − u(xn, n)| ≤ C ku0(·, n)kLp(S1)
implying that |ku(·, n)kLp(S1)− 1| → 0 as n → ∞. Since limt→∞e(t) exists, our
claim follows. After observing that d
dt(i − λ1e) ≤ 0 and t→+∞lim i(t) − λ1e(t) = 0 ,
we conclude that i − λ1e ≥ 0 at any t ≥ 0 and, as a special case, at t = 0,
for an arbitrary initial datum. This is already a sketch of an alternative proof of Theorem1. Because of its connection with the flow (8), the inequality i ≥ λ1e can
be considered as an entropy – entropy production inequality : see for instance [1]. So far, this second proof of Theorem 1 is formal as we did not establish the existence of the solutions to the parabolic problem nor the regularity which is needed to justify all steps. To make the proof rigorous, here are the main steps that have to be done:
1. Regularize the initial datum to make it as smooth as needed and bound it from below by a positive constant, and from above by another positive constant. 2. Regularize the operator by considering for instance the operator
u 7→ (p − 1) ε2+ |u0|2p2−1 u00 for an arbitrarily small ε > 0.
3. Prove estimates of the various norms based on the adapted (for ε > 0) equation and on entropy estimates as above, and establish that these estimates can be obtained uniformly in the limit as ε → 0.
4. Get inequalities (with degraded constants for ε > 0) and recover an entropy – entropy production inequality by taking the limit as ε → 0.
5. Conclude by density on the inital datum, in order to prove the result in the Sobolev space of Theorem1.
Details are out of the scope of the present paper. None of these steps is extremely difficult but lots of care is needed. Regularity and justification of the integrations by parts is a standard issue in this class of problems, see for instance the comments in [14, page 694]. Up to these technicalities which are left to the reader, this completes the second proof of Theorem1.
3.2. An improvement of the interpolation inequality. The parabolic ap-proach provides an easy improvement of (1) and (2). Let us consider the func-tion Ψp,q defined by Ψp,q(z) = z + (p − 1)2 2 p − 1 1 + q − p p − q z − 1 p − q log 1 + (p − q) z if p 6= q , Ψp,p(z) = z + (p − 1)2 2 (2 p − 1)z 2 if p = q .
The function Ψp,qis defined on R+, convex and such that Ψp,q(0) = 0 and Ψ0p,q(0) =
1. The flow approach provides us with an improved version of Theorem1.
Theorem 2. Assume that p ∈ (2, +∞) and q > p − 1. For any function u ∈ W1,p
(S1) \ {0}, the following inequalities hold:
ku0k2 Lp(S1)≥ λ1kuk2Lq(S1)Ψp,q 1 p − q kuk2 Lp(S1)− kuk2Lq(S1) kuk2 Lq(S1) ! if p 6= q, and ku0k2 Lp(S1)≥ λ1kuk2Lp(S1)Ψp,p 2 p Z S1 |u|p kukpLp(S1) log |u| kukLp(S1) dσ ! if p = q.
Proof. In the computations of Section 3.1, (9), we dropped the termR
S1 |u0|2p
up dσ. Actually, the Cauchy-Schwarz inequality
Z S1 |u0|pdσ 2 = Z S1 up2 · u− p 2|u0|pdσ 2 ≤ Z S1 updσ Z S1 |u0|2p up dσ
can be used as in [2] to prove that
Z S1 |u0|2p up dσ ≥ R S1|u 0|pdσ2 R S1u pdσ = ip kukpLp(S1) with i = ku0k2
Lp(S1) and, after recalling that e0= − 2 i, we deduce from (9) that
e00+ 2 λ1e0+ 2 κ
i e0
1 + (p − q) e ≥ 0
with κ = (p−1)2 p−12(1 + q − p). Here we assume that p 6= q and kukLq(S1)= 1 so that kuk2
Lp(S1) = 1 + (p − q) e by definition of e. Using the standard entropy – entropy production inequality i − λ1e ≥ 0, we deduce that
e00+ 2 λ1 1 + κ e 1 + (p − q) e e0≥ 0 ,
that is,
d
dt(i − λ1Ψp,q(e)) ≤ 0 ,
and the result again follows from limt→+∞i(t) − λ1Ψp,q e(t) = 0 if kukLq(S1)= 1. The general case is obtained by replacing u by u/kukLq(S1) = 1 while the case p = q is obtained by passing to the limit as q → p.
We notice that the equality in (1) can be achieved only by constants because i − λ1e ≥ λ1 Ψp,q(e) − e ≥ 0
and Ψp,q(z) − z = 0 is possible if and only if z = 0. This explains why the infimum
of i − λ1e, i.e., the infimum of Qλ1 and Q
λ1, is achieved only by constant functions. In the case p = q, let us notice that the improved interpolation inequality of Theorem2 can be written as
ku0k2 Lp(S1)≥ 2 λ1 p kuk 2−p Lp(S1) Z S1 |u|p log |u| kukLp(S1) dσ × 1 + (p − 1) 2 p (2 p − 1) Z S1 |u|p kukpLp(S1) log |u| kukLp(S1) dσ ! . In the case p 6= q, let us notice that the improved interpolation inequality of Theorem2 can be written as
ku0k2 Lp(S1)≥ λ1Kp,q e[u] kuk 2 Lp(S1)− kuk2Lq(S1) p − q , where Kp,q(s) := Ψp,q(s) s and e[u] := kuk2 Lp(S1)− kuk 2 Lq(S1) (p − q) kuk2 Lq(S1) ,
for any function u ∈ W1,p(S1) \ {0}. There is essentially no improvement for func-tions u such that e[u] is small because lims→0+Kp,q(s) = 1 , but s 7→ Kp,q(s) is monotone increasing and lims→+∞Kp,q(s) = 1 + κ.
3.3. Keller-Lieb-Thirring estimates. The nonlinear interpolation inequalities (3) and (6) can be used to get estimates of the ground state energy of Keller-Lieb-Thirring type as, for instance, in [8]. We are interested in the extension of the p = 2 case. In the case q > p, the question is to decide whether the quotient
u 7→ ku0k2 Lp(S1)− R S1V |u| pdσ2/p kuk2 Lp(S1)
can be bounded from below uniformly in u for a given potential V , in terms of an integral quantity depending only on V . In the case p = 2 this quotient is simply the Rayleigh quotient associated with the Schr¨odinger operator −dxd22 − V and its minimizer is, when it exists, the ground state. As in the case p = 2, we obtain a lower bound when p 6= 2 in a setting which is in one-to-one correspondance with the interpolation inequality (1). Let us give details.
In the range 2 < p < q, by applying H¨older’s inequality, we find that Z S1 V |u|pdσ ≤ kV k L q q−p(S1)kuk p Lq(S1).
We can rewrite (3) as ku0k2 Lp(S1)− µ kuk2Lq(S1)≥ − λ kuk2Lp(S1) with µ = kV k2/p L q
q−p(S1) and λ = λ(µ) computed as the inverse of the function λ 7→ µ(λ), according to Proposition 1. As a consequence of Propositions 1 and 2, we have the following estimate on the ground state energy.
Corollary 1. Assume that 2 < p < q. With the above notations, for any function V ∈ Lq−pq (S1) and any u ∈ W1,p(S1), we have the estimate
ku0k2 Lp(S1)− Z S1 V |u|pdσ 2/p ≥ − λ kV k2/p L q q−p(S1) kuk2 Lp(S1). Moreover, µ kV k2/p L q q−p(S1) = kV k2/p L q q−p(S1) if kV k 2/p L q q−p(S1)≤ λ1 q − p and in that case, the equality is realized if and only if V is constant.
If p > 2 and p − 1 < q < p, there is a similar estimate, which goes as follows. By applying H¨older’s inequality, we find that
Z S1 |u|qdσ =Z S1 V−qpV q p|u|qdσ ≤ Z S1 V−p−qq dσ 1−pqZ S1 V |u|pdσ qp so that Z S1 V |u|pdσ ≥ kV−1k−1 L q p−q(S1)kuk p Lq(S1). We can rewrite (6) as ku0k2 Lp(S1)+ µ kuk2Lq(S1)≥ λ(µ) kuk2Lp(S1) with µ = kV−1k−2/p L q p−q(S1)
and λ = λ(µ), according to Proposition 3. As a conse-quence of Propositions3and4, we have the following estimate on the ground state energy.
Corollary 2. Assume that p > 2 and p − 1 < q < p. With the above notations, for any function V such that V−1 ∈ Lp−qq (S1) and any u ∈ W1,p(S1), we have the estimate ku0k2 Lp(S1)+ Z S1 V |u|pdσ 2/p ≥ λ kV−1k−2/p L q p−q(S1) kuk2 Lp(S1). Moreover, λ kV−1k−2/p L q p−q(S1) = kV−1k−2/p L q p−q(S1) if kV −1k−2/p L q p−q(S1)≤ λ1 p − q and in that case, the equality is realized if and only if V is constant.
4. Numerical results. Equation (4) involves non-local terms, which raises a nu-merical difficulty. However, using the homogeneity and a scaling, it is possible to formulate an equivalent equation without non-local terms and use it to perform some numerical computations.
4.1. A reparametrization. A solution of (4) can be seen as 2π-periodic solution on R. By the rescaling u(x) = K f T 2π(x − x0) , (10)
we get that f solves − T 2π p ku0k2−pLp(S1)K p−1L pf + λ kuk2−pLp(S1)K p−1fp−1 = µ(λ) kuk2−q Lq(S1)K q−1fq−1.
We can adjust T so that T 2π p ku0k2−pLp(S1)= λ kuk 2−p Lp(S1) and K so that Kq−pµ(λ) kuk2−qLq(S1)= λ kuk 2−p Lp(S1). Altogether, this means that the function f now solves
− Lpf + fp−1 = fq−1 (11)
on R and is T -periodic. Equations (4) and (11) are actually equivalent.
Proposition 5. Assume that p ∈ (2, +∞) and q > p − 1. If u > 0 solves (4) and f is given by (10) with x0∈ R, T = 2π λ1p ku0k1−2p Lp(S1) kuk1− 2 p Lp(S1) and K = λ µ(λ) kukq−2Lq(S1) kukp−2Lp(S1) !q−p1 ,
then f solves (11) and it is T -periodic. Reciprocally, if f is a T -periodic positive solution of (11), then u given by (10) is, for an arbitrary x0∈ R, and an arbitrary
K > 0, a 2π-periodic positive solution of (4) with
λ = T 2π 2 kf kp−2 Lp(0,T ) kf0kp−2 Lp(0,T ) and µ(λ) = λ T2q−2p kf kq−2Lq(0,T ) kf kp−2Lp(0,T ) = T 2π 2 T2q−p2 kf kq−2Lq(0,T ) kf0kp−2 Lp(0,T ) .
Proof. To see that u(x) = f (T x /(2π)) solves (4), it is enough to write (11) in terms of u and use the change of variables to get that
ku0kLp(S1)= 1 2πT 1−1 pkf0kLp(0,T ), kukLp (S1)= T− 1 pkf kLp(0,T ), and kukLq(S1)= T− 1 qkf k Lq(0,T ). Notice that on S1, we use the uniform probability measure dσ, while on [0, T ] we
use the standard Lebesgue measure. We can of course translate u by x0 ∈ R or
multiply it by an arbitrary K > 0 (or an arbitrary K ∈ R if we relax the positivity condition).
Proposition2and Proposition5have a straightforward consequence on the period of the solutions of (11).
Corollary 3. Assume that 2 < p < q. If f is a non-constant periodic solution of (11) of period T , then T > 2 π s λ1 q − p kf0kp2−1 Lp(0,T ) kf kp2−1 Lp(0,T ) .
A similar result also holds in the case p > 2 and p − 1 < q < p.
4.2. A Hamiltonian reformulation. Assume that 2 < p < q. Eq. (11) can be reformulated as a Hamiltonian system by writing f = X and
Y = |X0|p−2X0 ⇐⇒ X0= |Y |p−1p −2Y , Y0= |X|p−2X − |X|q−2X . (12) The energy H(X, Y ) = (p − 1) |Y |p−1p +p q|X| q − |X|p
is conserved and positive solutions are determined by the condition min H =pq−1 ≤ H < 0. Hence a shooting method with initial data
X(0) = a and Y (0) = 0
provides all positive solutions (up to a translation) if a ∈ (0, 1]. For clarity, we shall denote the corresponding solution by Xaand Ya. Some solutions of the Hamiltonian
system and the corresponding vector field are shown in Fig.1.
-2 -1 0 1 2 -1.0 -0.5 0.0 0.5 1.0
Figure 1. The vector field (X, Y ) 7→ (|Y |p−1p −2Y, |X|p−2X − |X|q−2X) and periodic trajectories corresponding to a = 1.35
(with positive X) and a = 1.8 (with sign-changing X) are shown for p = 2.5 and q = 3. The zero-energy level is also shown.
The numerical computation of the branches. Assume that 2 < p < q and let us consider the solution of
− Lpfa+ fap−1 = f q−1 a , f
0
a(0) = 0 , fa(0) = a .
We learn from the Hamiltonian reformulation that H fa(r), |fa0(r)|p−2fa0(r)
is independent of r, where H(X, Y ) = (p − 1) |Y |p−1p + p V (X) where V (X) :=
1 q|X|
q−1 p|X|
p. Since we are interested only in positive solutions, it is necessary that
H(a, 0) < 0, which means that we can parametrize all non-constant solutions by a ∈ (0, 1). Let b(a) ∈ 1, (q/p)1/(q−p) be the other positive solution of V (b) = V (a).
If Ta denotes the period of fa, then we know that fa0 is positive on the interval
(0, Ta/2) and can compute it using the identity H fa(r), |fa0(r)|p−2fa0(r) = V (a)
as fa0(r) = p p − 1 V (a) − V fa(r) 1p . This allows to compute Ta as
Ta= 2 Z Ta/2 0 dr = Z b(a) a p p − 1 V (a) − V X −1p dX . See Fig.2. 0.2 0.4 0.6 0.8 1.0 2 4 6 8 10 12
Figure 2. The period Ta of the solution of (12) with initial
datum X(0) = a ∈ (0, 1) and Y (0) = 0 as a function of a for p = 3 and q = 5. We observe that lima→0Ta= +∞ and lima→1Ta= 0.
With the same change of variables X = fa(r), we can also compute
Z Ta 0 |fa0| pdr = 2Z b(a) a p p − 1 V (a) − V X 1−1p dX , Z Ta 0 |fa|pdr = Z b(a) a Xp p p − 1 V (a) − V X −1p dX , Z Ta 0 |fa|qdr = Z b(a) a Xq p p − 1 V (a) − V X −p1 dX .
Using Proposition 5, we can obtain the plot (λ, µ(λ)) as a curve parametrized by a ∈ (0, 1). See Fig.3. Similar results also hold in the case p > 2 and p − 1 < q < p.
0 1 2 3 4 5 0 1 2 3 4 5 0 1 2 3 4 5 0.0 0.2 0.4 0.6 0.8 1.0
Figure 3. Left: the branch λ 7→ µ(λ) for p = 3 and q = 5. Right: the curve λ 7→ λ−µ(λ). In both cases, the bifurcation point λ = λ? 1
is shown by a vertical line.
5. Concluding remarks and open questions. A major difference with the case p = 2 is that the 1-homogenous p-Laplacian flow (8) involves a nonlocal term, for homogeneity reasons. This is new and related with the fact that inequality (1) is 2-homogenous. To get rid of this constraint, one should consider inequalities with a different homogeneity, but then one would be in trouble when Taylor expanding at order two around the constants, and the framework should then be entirely different. Instead of using a 1-homogenous flow, one could use a non 1-homogenous flow as in [7], but one cannot expect that this would significantly remove the most important difficulty, namely that λ?
1 is a natural threshold for the perturbation of
the constants.
In Lemma1, we cannot replace λ1by λ?1, as it is shown in the Appendix: see the
discussion of the optimal constant in (5). On the other hand, in the computation of i0in Section3.1, the term that we drop: R
S1u
−p|u0|2pdσ, is definitely of lower order
in the asymptotic regime as t → +∞. Actually, in (5), if we consider u = 1 + ε v and investigate the limit as ε → 0+, it is clear that the inequality of Lemma 1
degenerates into the Poincar´e-Wirtinger inequality Z S1 (Lpv)2dσ ≥ λ1kv0k 2(p−1) Lp(S1) ∀ v ∈ W 2,p (S1) ,
where λ1 is not the optimal constant, as can be checked by writing the
Euler-Lagrange equation for an optimal w = |v0|p−2v. Altogether, it does not mean that
one cannot prove that the optimal constant Λp,q in Theorem 1is equal to λ?1 using
the carr´e du champ method, but if this can be done, it is going to be more subtle than the usual cases of application of this technique.
Finally let us point that it is a very natural and open question to ask if there is an analogue of the Poincar´e estimate of Lemma 1 if p ∈ (1, 2). If yes, then we would also have an analogue of Theorem1with 1 < p < 2. Notice that this issue is not covered in [13].
Appendix A. Considerations on some inequalities of interest. We assume that p > 1. In this appendix we collect some observations on the various inequalities
which appear in this paper and how the corresponding optimal constants are related to each other.
• Spectral gap associated with Lp. On S1, L−1p (0) is generated by the constant
functions and there is a spectral gap, so that we have the Poincar´e inequality Z S1 |u0|pdσ ≥ Λ 1 Z S1 |u|pdσ ∀ u ∈ W1,p (S1) such that Z S1 |u|p−2u dσ = 0 . (13) The optimal constant Λ1 is characterized by solving the Cauchy problem
Lpu + |u|p−2u = 0 with u(0) = 1 and u0(0) = 0
and performing the appropriate scaling so that the solution is 2π-periodic, as follows. Let φp(s) = |s|p/p and denote by p0 = p/(p − 1) the conjugate exponent. Since the
ODE can be rewritten as: φ0p(u0)0
+ φ0p(u) = 0, we can introduce v = φ0p(u0) and observe that (u, v) solves the system
u0= φ0p0(v) , v0= − φ0p(u) , u(0) = 1 , v(0) = 0 .
The Hamiltonian energy φp(u) + φp0(v) = 1/p is conserved and a simple phase plane analysis shows that the solution is periodic, with a period which depends on p and is sometimes denoted by 2πp in the literature. Then the function x 7→ fp(x) :=
u(πpx/π) is 2π-periodic and solves
Lpfp+ Λ1|fp|p−2fp= 0 with Λ1=
π πp
p . See [11,12] for more results on Λ1 and related issues.
For any function u ∈ W1,p
(S1), t 7→ R
S1|t + u|
pdσ is a convex function which
achieves its minimum at t = 0 ifR
S1|u|
p−2u dσ = 0. As a consequence, we get that
Λ1= min u∈W1,p(S1)maxt∈R ku0kp Lp(S1) kt + ukpLp(S1) and λ1= inf v∈W1 kv0k2 Lp(S1) kvk2 Lp(S1) ≤ Λ 2 p 1 .
On the other hand, the optimal function fp is in W1by uniqueness of the solution
to the ODE. Indeed we know that fp changes sign and for any x0 ∈ R such that
fp(x0) = 0, then x 7→ − fp(2 x0− x) is also a solution, which coincides with fp.
Hence we have that
λ1= Λ
2 p
1 .
Alternatively, λ1 is the optimal constant in the inequality
kv0k2
Lp(S1)≥ λ1kvkL2p(S1) ∀ v ∈ W1. (14)
Notice that the zero average conditionR
S1|u|
p−2u dσ = 0 in (13) differs from the
conditionR
S1v dσ = 0 in (14), but that the two inequalities share the same optimal
• The inequality on L2
(S1). Here we consider the inequality kv0k2 Lp(S1)≥ λ ? 1kvk 2 L2(S1) ∀ v ∈ W1, (15)
with optimal constant λ?
1. Since dσ is a probability measure, then kuk2Lp(S1)− kuk2
L2(S1) has the same sign as (p − 2) and we have equality if and only if u is constant, so that, for any p 6= 2, we have (p − 2) λ?1− λ1 ≥ 0 as already noted
in the introduction. If p = 2, we have of course λ?1 = λ1 as the two inequalities
coincide. If p 6= 2, one can characterize λ?1 by solving the Cauchy problem
Lpu + u = 0 with u(0) = 1 and u0(0) = 0
and performing the appropriate scaling so that the solution is 2π-periodic, as it has been done above for Λ1. We can also introduce v = φ0p(u0) and observe that (u, v)
solves the system
u0 = φ0p0(v) , v0 = − u , u(0) = 1 , v(0) = 0 ,
so that trajectories differ from the ones associated with fp. This proves that λ?16= λ1
if p 6= 2. See AppendixBfor further details.
• A more advanced interpolation inequality. In the proof of Lemma1, we establish on W1,p (S1) the inequality ku0k2 Lp(S1)kuk p−2 Lp(S1)≥ λ1 Z S1 |u|p−2v2dσ with v = u − ¯u , u =¯ Z S1 u dσ (16) in the case p > 2. This inequality is optimal because equality is achieved by u = fp.
We can in principle consider the inequality ku0k2 Lp(S1)kuk p−2 Lp(S1)− µ1 Z S1 |u|p−2v2dσ ≥ 0 ∀ u ∈ W1,p (S1)
with optimal constant µ1and v = u − ¯u, for some appropriate notion of average ¯u
which is not necessarily given by ¯u =R
S1u dσ. With the standard definition of ¯u,
we have shown in Lemma1that µ1= λ1. Any improvement on the estimate of µ1
(with an appropriate orthogonality condition), i.e., a condition such that fp is not
optimal and µ1> λ1, would automatically provide us with the improved estimate
Λp,q ≥ µ1
in Theorem1. As a consequence of Theorem1, we know anyway that µ1≤ λ?1.
Inspired by the considerations on Λ1, let us define
µ1= min u∈W1,p(S1)maxt∈R ku0k2 Lp(S1)kuk p−2 Lp(S1) R S1|u| p−2|u − t|2dσ.
An elementary optimization on t shows that the optimal value is t = ¯upwith
¯ up:= R S1|u| p−2u dσ R S1|u| p−2dσ .
By considering again fp, we see that actually µ1= λ1, which proves the inequality
ku0k2 Lp(S1)kuk p−2 Lp(S1)≥ λ1 Z S1 |u|p−2|u − ¯u p|2dσ ∀ u ∈ W1,p(S1) (17)
for an arbitrary p > 2. As a consequence of (17), we recover (5). By keeping track of the equality case in the proof, we obtain that fprealizes the equality in (5), which
Appendix B. Computation of the constants λ1 and λ?1. Any critical point
associated with λ1 solves
− Lpu = λ p 2 1 |u| p−2u on S1≈ [0, 2π) . The function f such that
u(x) = f T1x 2 π x ∈ [0, T1) , T1 2 π p = λ p 2 1 is a T1-periodic solution of − Lpf = |f |p−2f .
Moreover, by homogeneity and translation invariance, we can assume that f (0) = 1 and f0(0) = 0. An analysis in the phase space shows that f has symmetry properties and that the energy is conserved and such that (p − 1) |f0|p+ |f |p= 1, so that
T1= 4 Z 1 0 p − 1 1 − Xp 1p dX . Hence we conclude (see Fig.4) that
λ1= 2 π Z 1 0 p − 1 1 − Xp 1p dX !2 . Similarly, a critical point associated with λ?
1solves
− ku0k2−pLp(S1)Lpu = λ?1u on S 1
≈ [0, 2π) .
With no loss of generality, by homogeneity we can assume that ku0k2−pLp(S1)= λ?1 so
that u can be considered as 2π-periodic solution on R of − Lpu = u. By translation
invariance, we can also assume that u0(0) = 0 but the value of u(0) = a > 0 is unknown. The function f such that
u(x) = a fa2p−1x
is still a periodic solution of
− Lpf = f ,
with now f (0) = 1 and f0(0) = 0, of period T1?= 2 π ap2−1.
The energy 2p(p − 1) |f0|p+ |f |2= 1 is conserved, so that
T1?= 4 Z 1 0 2 p p − 1 1 − X2 1p dX and a2p−1 = 2 π Z 1 0 2 p p − 1 1 − X2 1p dX . By computing ku0kpLp(S1)= 4 a 3−2 p Z T1?/4 0 |f0|p dx 2 π = 2 πa 3−2 p Z 1 0 2 p p − 1 1 − X2 1p−1 dX , we obtain (see Fig.4) that
λ?1= ku0k2−pLp(S1)= 2 π Z 1 0 2 p p − 1 1 − X2 1p−1 dX !2p−1 2 π Z 1 0 2 p p − 1 1 − X2 1p!3− 2 p .
2 4 6 8 10 0.2 0.4 0.6 0.8 1.0 1.2
Figure 4. The curves p 7→ λ1 (dotted) and p 7→ λ?1 (plain) differ.
Acknowledgment: J.D. has been partially supported by the Project EFI (ANR-17-CE40-0030) of the French National Research Agency (ANR), and also acknowl-edges support from the Prefalc project CFRRMA. M.G-H and R.M. have been supported by Fondecyt grant 1160540.
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